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Motivation: Genome-wide association studies (GWAS) have identified many lociimplicated in disease susceptibility. Integration of GWAS summary statistics (pvalues) and functional genomic datasets should help to elucidate mechanisms.Results: We describe the extension of a previously described non-parametricmethod to test whether GWAS signals are enriched in functionally defined locito a situation where only GWAS p values are available. The approach isimplemented in VSEAMS, a freely available software pipeline. We use VSEAMS tointegrate functional gene sets defined via transcription factor knock downexperiments with GWAS results for type 1 diabetes and find variant setenrichment in gene sets associated with IKZF3, BATF and ESRRA. IKZF3 lies in aknown T1D susceptibility region, whilst BATF and ESRRA overlap other immunedisease susceptibility regions, validating our approach and suggesting novelavenues of research for type 1 diabetes. Availability and implementation:VSEAMS is available for download http://github.com/ollyburren/vseams.

bioinformatics

VSEAMS: A pipeline for variant set enrichment analysis using summary  GWAS data identifies IKZF3, BATF and ESRRA as key transcription factors in  type 1 diabetes